Retail CIOs are building an omnichannel network to reach their customers in multiple ways. The looming challenge remains the unparalleled speed of changing dynamics, driven primarily by a savvier and demanding new generation of shoppers. With this, CIOs in the retail industry today are facing a 'do or die' situation with building and introducing novel digital experiences for customers.

Although online sales for retailers are growing exponentially, there is still very strong interest in shopping at brick and mortar stores. However, the dynamics have grown to a complex juxtaposition — where apart from being able to securely shop online from their favorite retailer, the customer also wants to have the ability to walk into a store location and have an ultra-rich digital experience that establishes an intimate relationship.

'Have you ever come up with a fantastic new business idea only to later realize that dozens of people are already doing it? You are not alone. If there is a business opportunity in offering a product or service, there are people doing it already. Waiting for an idea that is not only highly profitable but also has no competition is akin to a unicorn sighting.

A better strategy is to differentiate yourself in a profitable market where there is tons of competition. When customers see a unique value in what you offer, they are more likely to buy from you. A number of popular and successful businesses became what they are today thanks to this strategy.

There are plenty of examples for ideas on how to differentiate yourself.'

Fact: virtually everything your customers do on your website or mobile app produces data; data that not only can be leveraged to create marketing strategies and boost conversions but also increase your bottom line. All that is needed is an efficient way of both storing and employing the data. This is where Data Management Platforms (or DMPs) come in handy.

In this white paper, Mopinion talks about the criticality of offering a personalised journey to online customers, how customer profiles are driven by digital feedback, as well as how to collect, analyse and report on both feedback data and customer data (with lots of practical tips).

Have you ever made a purchase online following someone’s advice? What about the recommendations that were prompted to you by the website itself? Being quite a common element of an eCommerce app, tailored product recommendations have proven to be an extremely effective tool for revenue growth.

Namely, Amazon’s recommendation engine is said to generate 35% of the platform’s total revenue. Taking into account its actual sales volume ($178 billion in 2017), this makes an additional $62 billion per year. Quite impressive, right?

Yet, eCommerce recommendation engines represent only one example of app personalization strategies. There are many more use cases any digital business can put to use.

In this article, we will shed some light on several of the proven mobile app personalization tactics and real-life examples to help you spur your imagination.

Admit it. We as consumers are a demanding bunch. We have high expectations of the brands around us – whether that’s simply knowing our preferences, tailoring our online journeys, individualizing communications, or providing quick and hassle-free customer support. Put simply, we want to be the apple of every business’ eye. If things don’t go our way, well….it won’t be long before we’re off looking for an alternative that will meet our expectations. This logic is precisely why personalization efforts are so critical to the success of businesses – especially in the digital era.

Being able to provide these personalized experiences, however, has proven to be a real challenge among many digital marketers who are still in the process of adjusting to this growing trend. In fact, almost 60% of marketers claim that they struggle to personalize content (in real-time); an occurrence which is often attributed to the company’s inability to gain customer insights quickly enough and apply them. One way of removing this hurdle and gathering the necessary information for personalizing is by collecting customer feedback.

Let’s take a closer look at how customer feedback data drives the three ‘breeds’ of personalization.

Mobile, and increasingly apps, are core to the success of any retailer's strategy through all stages of the path to purchase or shopping customer's experience, from initial research through to completing their purchase.

Year on year, app store trends have seen sustained a growth in shopping apps. This has created awareness amongst retailers that a mobile presence is imperative, however, what can marketers do to ensure that the mobile consumer acquired stays loyal to the channel?

In today’s competitive e-commerce environment, personalizing the customer experience is the number one priority: To drive conversion, the right message needs to be sent to the right person at the right time. How do you accomplish that? Increasingly, AI is emerging as the best way to offer a truly one-to-one experience to customers. A Gartner study notes that “by 2020, 85% of customer interactions will be managed without a human” and that by 2040, “more than 40% of all data analytics projects will relate to an aspect of customer experience.” So what does that look like?

More shopping on mobile amplifies a persistent problem for online retailers. Growing cart abandonment. Research from Barilliance, an eCommerce personalization tools developer, illuminates the challenge.

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Mopinion: The Leading User Experience Tool

Mopinion is a proud sponsor of User Experience News. The voice of the online user is taking on an increasingly important role when it comes to improving websites and apps. So web analysts and digital marketeers are making more and more use of User Experience Tools in order to collect experience from the user. Mopinion takes it one step further and offers a solution to analyse and visualise User Experience results from your websites and apps wherever you need them. The real challenge for companies is not about capturing experience, it is about how to make sense of the data.